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  1. FDA STEM Outreach, Education and Engagement

Application of the minimal physiologically based pharmacokinetic (mPBPK) model with a zonal liver compartment for the prediction of drug concentrations in human liver

Authors:
Poster Author(s)
Tai Huynh; (student) Kiara Fairman; Minjun Chen; Annie Lumen; Miao Li (mentor), FDA/NCTR
Center:
Contributing Office
National Center for Toxicological Research

Abstract

Poster Abstract

The physiologically based pharmacokinetic (PBPK) model is a computational model using mathematical equations to describe physiological and biochemical processes. It is a valuable tool to predict drug absorption, distribution, metabolism, and excretion in humans and different animal species. The PBPK models are well accepted by the FDA for new drug applications and regulatory decisions related to dose optimization and drug-drug interactions. The whole-body PBPK model consists of compartments that represent all different organs or tissues. Due to the lack of drug concentrations in organs from clinical pharmacokinetic (PK) studies, the whole-body PBPK model may lead to more uncertainties. On the other hand, the minimal PBPK (mPBPK) model reduces the number of compartments by grouping organs with similar kinetics into one compartment. The mPBPK model also has the advantage of using PK parameters reported by experimental PK studies as model parameters. By considering drug distribution to specific organs, the mPBPK model can provide detailed descriptions of drug disposition. The zonal liver model adapted to mPBPK can help to predict drug concentrations at different liver zone areas, which is closely related to the risk leading drug induced liver injury (DILI). The objective of this study is to establish a mPBPK model with a zonal liver compartment to predict drug concentrations in human liver and to facilitate the prediction of risk for DILI. The mPBPK model has been constructed with the richly perfused, poorly perfused and liver compartments. The physiological parameters were from previous literature, and drug specific parameters are from PK studies or parameter estimations. The model was applied to predict drug concentrations in plasma and liver, and to calculate the accumulation factor for drugs. The accumulation factor can be used to estimate real drug exposure in liver which can lead to the liver injury. Here we used amiodarone, pentamidine and tacrolimus, which have the potentials to cause DILI, as case studies in this model. By establishing the zonal liver compartment based on previous experimental data, the model can be used to predict drug concentrations at different zones of liver.

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